扩散峰度成像与DWI在卵巢实性病灶良恶性鉴别诊断中的应用  被引量:4

Comparison of the application of diffusion kurtosis imaging and DWI in the differential diagnosis of benign and malignant ovarian lesions

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作  者:郭娟娟 GUO Juanjuan(Department of Imaging,988 Hospital of the Joint Logistics Support Force of the Chinese People’s Liberation Army,Zhengzhou 450000,China)

机构地区:[1]中国人民解放军联勤保障部队第九八八医院影像医学科,河南郑州450000

出  处:《中国中西医结合影像学杂志》2021年第2期140-142,共3页Chinese Imaging Journal of Integrated Traditional and Western Medicine

摘  要:目的:探讨扩散峰度成像(DKI)与DWI在卵巢实性病灶良恶性鉴别诊断中的应用价值。方法:回顾性分析87例卵巢实性病灶的临床及影像资料,患者均行卵巢MRI常规平扫、DWI、DKI检查,分别获取ADC值、平均扩散峰度(MK)和平均扩散率(MD),评估DWI、DKI对卵巢良恶性病变的鉴别诊断价值。结果:与卵巢恶性病变相比,卵巢良性病变的ADC值、MD明显升高,MK明显降低(均P<0.05)。ADC、MK、MD联合诊断卵巢良恶性病变的AUC较三者单独及MK联合MD诊断诊断的AUC大。结论:与DWI相比,DKI对卵巢良恶性病变鉴别诊断价值略高;DWI联合DKI可提高对卵巢良恶性病变鉴别诊断效能及卵巢实性病灶检出率。Objective:To explore the application value of diffusion kurtosis imaging(DKI)and DWI in the differential diagnosis of benign and malignant ovarian lesions.Methods:The clinical data of 87 patients with surgery and pathology confirmed benign and malignant ovarian lesions were retrospectively analyzed.All patients were examined with ovary conventional MRI,DWI and DKI to obtain the ADC value,mean kurtosis(MK)and mean diffusivity(MD).The value of DWI and DKI in the differential diagnosis of benign and malignant ovarian lesions was evaluated.Results:The ADC values and MD were significantly higher,while MK was significantly lower in patients with benign ovarian lesions than those with malignant lesions(all P<0.05).The AUC of combination of the three for diagnosing benign and malignant ovarian tumors was larger than that of MK combined with MD,ADC value,MK or MD.Conclusions:Compared with DWI,DKI is slightly more valuable in the differential diagnosis of benign and malignant ovarian lesions.However,DWI combined with DKI can improve the efficiency for differential diagnosis of benign and malignant ovarian lesions and the accurate detection rate of ovarian solid lesions.

关 键 词:卵巢肿瘤 磁共振成像 诊断 鉴别 

分 类 号:R737.31[医药卫生—肿瘤] R445.2[医药卫生—临床医学]

 

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